Hypothesis Engine: Autonomous Literature-to-Hypothesis Workflows
NEO built a research helper that reads papers and data, sketches testable ideas, and drafts experiment plans. Humans still review, but you spend less time stuck between reading and designing the next run.
Problem Statement
We asked NEO to connect literature search, structured extraction, and hypothesis generation so people move from reading to experiment design faster, with provenance on every claim.
Solution Overview
- Corpus ingest: PDFs, arXiv, and tabular datasets.
- Synthesis: Map claims, gaps, and contradictions.
- Hypothesis cards: Testable predictions with suggested methods.
Workflow / Pipeline
| Step | Description |
|---|---|
| 1. Collect | Ingest sources and metadata |
| 2. Extract | Key findings, methods, and limitations |
| 3. Generate | Novel hypotheses ranked by feasibility and impact |
| 4. Plan | Draft protocols and evaluation metrics |
Repository & Artifacts
Generated Artifacts:
- Research pipeline CLI and structured outputs
- Citation graph and hypothesis ledger